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Candelaria Mosquera
Candelaria Mosquera
Verified email at hospitalitaliano.org.ar
Title
Cited by
Cited by
Year
Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis
N Gaggion, L Mansilla, C Mosquera, DH Milone, E Ferrante
IEEE Transactions on Medical Imaging 42 (2), 546-556, 2022
452022
Chest x-ray automated triage: A semiologic approach designed for clinical implementation, exploiting different types of labels through a combination of four Deep Learning …
C Mosquera, FN Diaz, F Binder, JM Rabellino, SE Benitez, AD Beresñak, ...
Computer Methods and Programs in Biomedicine 206, 106130, 2021
142021
Towards unraveling calibration biases in medical image analysis
MA Ricci Lara, C Mosquera, E Ferrante, R Echeveste
Workshop on Clinical Image-Based Procedures, 132-141, 2023
102023
CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images
N Gaggion, C Mosquera, L Mansilla, JM Saidman, M Aineseder, ...
Scientific Data 11 (1), 511, 2024
72024
User satisfaction with an AI system for chest X-Ray analysis implemented in a hospital’s emergency setting
D Rabinovich, C Mosquera, P Torrens, M Aineseder, S Benitez
Challenges of Trustable AI and Added-Value on Health, 8-12, 2022
72022
Impact of class imbalance on chest x-ray classifiers: towards better evaluation practices for discrimination and calibration performance
C Mosquera, L Ferrer, D Milone, D Luna, E Ferrante
arXiv preprint arXiv:2112.12843, 2021
62021
Integration of a deep learning system for automated chest x-ray interpretation in the emergency department: A proof-of-concept
C Mosquera, F Binder, FN Diaz, A Seehaus, G Ducrey, JA Ocantos, ...
Intelligence-Based Medicine 5, 100039, 2021
52021
Class imbalance on medical image classification: Towards better evaluation practices for discrimination and calibration performance
C Mosquera, L Ferrer, DH Milone, D Luna, E Ferrante
European Radiology 34 (12), 7895-7903, 2024
42024
Introducing Computer Vision into Healthcare Workflows
C Mosquera, MAR Lara, FN Díaz, F Binder, SE Benitez
Digital Health: From Assumptions to Implementations, 43-62, 2023
32023
Measuring the delay in the referral of unstable vertebral metastasis to the spine surgeon: a retrospective study in a Latin American institution
F Landriel, FP Lichtenberger, L Ulloque-Caamaño, C Mosquera, ...
Neurology India 71 (5), 902-906, 2023
22023
Three-dimensional printing and navigation in bone tumor resection
LE Ritacco, C Mosquera, I Albergo, DL Muscolo, GL Farfalli, MA Ayerza, ...
3D Printing, 2018
12018
Artificial Intelligence Assistance for the Measurement of Full Alignment Parameters in Whole-Spine Lateral Radiographs
F Landriel, BC Franchi, C Mosquera, FP Lichtenberger, S Benitez, ...
World Neurosurgery, 2024
2024
Towards unraveling calibration biases in medical image analysis
M Agustina Ricci Lara, C Mosquera, E Ferrante, R Echeveste
arXiv e-prints, arXiv: 2305.05101, 2023
2023
39P OLIMPIA dataset: Radiomics to predict outcomes in EGFR-mutant non-small cell lung cancer
G Pérez, JN Minatta, M Aineseder, C Mosquera, SE Benitez
Annals of Oncology 33, S18, 2022
2022
Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis
RN Gaggion Zulpo, LA Mansilla, C Mosquera, DH Milone, E Ferrante
Institute of Electrical and Electronics Engineers, 2022
2022
P60. 05 Radiomic Signature to Predict Outcomes in EGFR-Mutant Non-Small Cell Lung Cancer
JN Minatta, D Deza, M Aineseder, MM Nuñez, C Mosquera, L Lupinacci, ...
Journal of Thoracic Oncology 16 (10), S1166, 2021
2021
1174P Preliminary prediction of EGFR-mutant non-small cell lung cancer outcome using radiomic signature
JN Minatta, C Mosquera, M Aineseder, MAM Nuñez, D Deza, L Lupinacci, ...
Annals of Oncology 32, S941-S942, 2021
2021
Understanding the impact of class imbalance on the performance of chest x-ray image classifiers.
C Mosquera, L Ferrer, DH Milone, DR Luna, E Ferrante
CoRR, 2021
2021
Chest x-ray automated triage: a semiologic approach designed for clinical implementation, exploiting different types of labels through a combination of four Deep Learning …
C Mosquera, FN Diaz, F Binder, JM Rabellino, SE Benitez, AD Beresñak, ...
arXiv preprint arXiv:2012.12712, 2020
2020
FOUR DEEP LEARNING ARCHITECTURES.
C Mosquera, F Diaz, F Binder, JM Rabellino, SE Benitez, A Beresñak, ...
arXiv preprint arXiv:2012.12712, 2020
2020
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